Co-constructing knowledge with youth: what high-school aged mentors say and do to support their mentees’ autonomy, belonging, and competence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Self-Determination Theory’s (SDT) most recent ‘mini-theory,’ Relationships Motivation Theory (RMT) focuses on the essential ingredients of high-quality relationships (i.e. feelings of autonomy, belonging, and competence). This study explores the applicability of RMT to cross-age peer mentoring. Of particular interest was whether the RMT framework could help high-school mentors develop positive relationships with their elementary-aged mentees. The specific language and strategies mentors used to support feelings of autonomy, belonging, and competence was also of interest, as this level of detail has not been captured in previous research. High-school mentors were invited to learn about RMT during skill-building sessions. They were then asked to apply the language and skills they co-developed during mentoring sessions. Data included audio recordings of dyadic interactions, weekly mentoring logs, and interviews. Descriptive, Provisional, and In-Vivo coding were used to analyze data. Qualitative coding indicated high-school mentors were capable of co-constructing language and practices to support mentees’ feelings of autonomy, belonging, and competence. Findings also indicated that mentors successfully applied this knowledge to mentoring sessions. Weekly mentoring logs indicated skill-building sessions helped mentors develop positive relationships with their mentees. The results of this study begin to suggest that RMT can help inform the cross-age peer mentoring process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it